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Transmurale patiëntveiligheid Zijn medicatieveranderingen door de specialist terug te vinden in het dossier van de huisarts? Judith Poldervaart UMC Utrecht Post-doc patiëntveiligheid Huisarts in opleiding

Introductie 2 werelden Transmurale zorg = gevaar voor patiëntveiligheid Slechte communicatie Onduidelijke taakverdeling Patiënt: tussen wal en schip Toename aantal transities + toename medicatiegebruik = uitdaging TIPP houdt zich bezig met verbeteren transmurale patientveiligheid.

Methode Doel: medicatieverandering in ziekenhuis terugvinden in HA dossier Design: dossierstudie Cardiologie MDL UMC Utrecht + Huisartsen Utrecht Stad

Methode Patiënten die in 2013: Transitie? Medicatiewijziging? - In UMCU bij CAR/MDL zijn geweest - Stonden ingeschreven bij HA in regio Transitie? Opname Policontact Medicatiewijziging? Soort wijziging Medicijn Medicijn groep Documentatie HA? Aanwezig/correct? Tijdigheid?

Resultaten N=390 dossiers (leeftijd 59j, 54% man) 1100 transities; 408 medicatiewijzigingen  126 (31%) afwezig/incorrect in HA dossier Vaker bij MDL patiënten en jonge patiënten Tijdigheid 26% binnen 1 dag 55% binnen 3 maanden Results: Records of 390 patients included one or more primary-secondary care transitions; in total we identified 1511 transitions. During these transitions, 408 in-hospital prescription changes were made, of which 31% was not or incorrectly documented in the medical record of the primary care provider within the next 3 months. In case changes were documented, the median number of days between hospital visit and documentation was 3 (IQR 0-18). Conclusions: One third of in-hospital prescription changes was not or incorrectly documented in the primary care provider’s record, which likely puts patients at risk of adverse drug events after hospital visits. Such flawed reliability of a routine care process is unacceptable and warrants improvement and close monitoring. 183 (55.3%)

Discussie Interpretatie Limitatie Implicatie Slechte documentatie ≠ slechte kwaliteit van zorg Echter: risico op fouten en inefficiënt Limitatie Dossierstudie Implicatie Twee systemen, geen optimale overdracht Welke veranderingen op systeemniveau verbeteren uitkomsten in de praktijk?

genoteerd bij huisarts Resultaten Afdeling Medicatiegroepen Afwezig of incorrect genoteerd bij huisarts (N=126) Cardiologie 1. Beta-blockers 16 (26.7%) 2. Diuretica 16 (32.7%) 3. Plaatjesremmers 7 (18.9%) Anders 33 (23.1%) MDL 1. Laxantia 15 (55.6%) 2. Protonpompremmers 8 (38.1%) 3. IBD ontstekingsremmers 8 (80.0%) 23 (37.1%) Dia 7: zeg je daarbij nog iets over de mogelijke consequenties van fouten met deze groepen medicatie? Of misschien bij dia 8 interpretatie (puntje 2). Results: Records of 390 patients included one or more primary-secondary care transitions; in total we identified 1511 transitions. During these transitions, 408 in-hospital prescription changes were made, of which 31% was not or incorrectly documented in the medical record of the primary care provider within the next 3 months. In case changes were documented, the median number of days between hospital visit and documentation was 3 (IQR 0-18). Conclusions: One third of in-hospital prescription changes was not or incorrectly documented in the primary care provider’s record, which likely puts patients at risk of adverse drug events after hospital visits. Such flawed reliability of a routine care process is unacceptable and warrants improvement and close monitoring. 183 (55.3%)

tijdigheid Documentation Start1 n= 220 Stop2 n= 77 Dose/freq change3   n= 220 Stop2 n= 77 Dose/freq change3 n= 87 Switch4 n= 24 Total n= 408/331** Prescription overview Number of days, median (IQR)* 2 (0-16) n/a≠ 5 (0-33) 2 (1-14) 3 (0-18) ≤ 1 day 64 (29.1%) n/a 15 (17.2%) 6 (25.0%) 85 (25.7%) ≤ 2 weeks 99 (45.0%) 24 (27.6%) 12 (50.0%) 135 (40.8%) ≤ 3 months 129 (58.6%) 37 (42.5%) 16 (66.7%) 183 (55.3%) Free text fields 7 (4-14) 3.0 (1-9) 4 (1-24) 2 (1-8) 5 (2-14)

subgroepen Total number of prescription changes Correct documentation   Total number of prescription changes Correct documentation Inadequate documentation No documentation Sex Women Men n=187 n=221 38 (20.3%) 48 (21.7%) 93 (49.7%) 103 (46.6%) 56 (30.0%) 70 (31.7%) Age ≤45 46-64 ≥65 n=68 n=144 n=196 5 (7.4%) 30 (20.8%) 51 (26.0%) 36 (52.9%) 62 (43.1%) 98 (50.0%) 27 (39.7%) 52 (36.1%) 47 (24.0%) Department Cardiology Gastroenterology n=289 n=119 69 (23.9%) 17 (14.3%) 148(51.2%) 48 (40.3%) 72 (24.9%) 54 (45.4%)